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// Auf Groestlcoin spezialisierte Version von Groestl inkl. Bitslice
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#include <stdio.h>
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#include <memory.h>
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#include "cuda_helper.h"
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#ifdef __INTELLISENSE__
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#define __CUDA_ARCH__ 500
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#define __byte_perm(x,y,n) x
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#endif
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#include "miner.h"
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__constant__ uint32_t pTarget[8]; // Single GPU
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__constant__ uint32_t groestlcoin_gpu_msg[32];
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static uint32_t *d_resultNonce[MAX_GPUS];
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#if __CUDA_ARCH__ >= 300
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// 64 Registers Variant for Compute 3.0+
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#include "quark/groestl_functions_quad.h"
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#include "quark/groestl_transf_quad.h"
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#endif
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#define SWAB32(x) cuda_swab32(x)
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__global__ __launch_bounds__(256, 4)
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void groestlcoin_gpu_hash_quad(uint32_t threads, uint32_t startNounce, uint32_t *resNounce)
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{
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#if __CUDA_ARCH__ >= 300
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// durch 4 dividieren, weil jeweils 4 Threads zusammen ein Hash berechnen
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uint32_t thread = (blockDim.x * blockIdx.x + threadIdx.x) / 4;
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if (thread < threads)
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{
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// GROESTL
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uint32_t paddedInput[8];
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#pragma unroll 8
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for(int k=0;k<8;k++) paddedInput[k] = groestlcoin_gpu_msg[4*k+threadIdx.x%4];
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uint32_t nounce = startNounce + thread;
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if ((threadIdx.x % 4) == 3)
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paddedInput[4] = SWAB32(nounce); // 4*4+3 = 19
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uint32_t msgBitsliced[8];
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to_bitslice_quad(paddedInput, msgBitsliced);
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uint32_t state[8];
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for (int round=0; round<2; round++)
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{
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groestl512_progressMessage_quad(state, msgBitsliced);
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if (round < 1)
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{
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// Verkettung zweier Runden inclusive Padding.
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msgBitsliced[ 0] = __byte_perm(state[ 0], 0x00800100, 0x4341 + ((threadIdx.x%4)==3)*0x2000);
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msgBitsliced[ 1] = __byte_perm(state[ 1], 0x00800100, 0x4341);
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msgBitsliced[ 2] = __byte_perm(state[ 2], 0x00800100, 0x4341);
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msgBitsliced[ 3] = __byte_perm(state[ 3], 0x00800100, 0x4341);
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msgBitsliced[ 4] = __byte_perm(state[ 4], 0x00800100, 0x4341);
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msgBitsliced[ 5] = __byte_perm(state[ 5], 0x00800100, 0x4341);
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msgBitsliced[ 6] = __byte_perm(state[ 6], 0x00800100, 0x4341);
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msgBitsliced[ 7] = __byte_perm(state[ 7], 0x00800100, 0x4341 + ((threadIdx.x%4)==0)*0x0010);
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}
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}
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// Nur der erste von jeweils 4 Threads bekommt das Ergebns-Hash
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uint32_t out_state[16];
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from_bitslice_quad(state, out_state);
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if (threadIdx.x % 4 == 0)
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{
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int i, position = -1;
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bool rc = true;
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#pragma unroll 8
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for (i = 7; i >= 0; i--) {
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if (out_state[i] > pTarget[i]) {
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if(position < i) {
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position = i;
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rc = false;
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}
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}
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if (out_state[i] < pTarget[i]) {
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if(position < i) {
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position = i;
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rc = true;
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}
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}
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}
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if(rc && resNounce[0] > nounce)
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resNounce[0] = nounce;
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}
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}
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#endif
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}
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__host__
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void groestlcoin_cpu_init(int thr_id, uint32_t threads)
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{
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// to check if the binary supports SM3+
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cuda_get_arch(thr_id);
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CUDA_SAFE_CALL(cudaMalloc(&d_resultNonce[thr_id], sizeof(uint32_t)));
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}
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__host__
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void groestlcoin_cpu_free(int thr_id)
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{
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cudaFree(d_resultNonce[thr_id]);
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}
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__host__
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void groestlcoin_cpu_setBlock(int thr_id, void *data, void *pTargetIn)
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{
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uint32_t msgBlock[32] = { 0 };
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memcpy(&msgBlock[0], data, 80);
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// Erweitere die Nachricht auf den Nachrichtenblock (padding)
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// Unsere Nachricht hat 80 Byte
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msgBlock[20] = 0x80;
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msgBlock[31] = 0x01000000;
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// groestl512 braucht hierfür keinen CPU-Code (die einzige Runde wird
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// auf der GPU ausgeführt)
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// Blockheader setzen (korrekte Nonce und Hefty Hash fehlen da drin noch)
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cudaMemcpyToSymbol(groestlcoin_gpu_msg, msgBlock, 128);
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cudaMemset(d_resultNonce[thr_id], 0xFF, sizeof(uint32_t));
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cudaMemcpyToSymbol(pTarget, pTargetIn, 32);
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}
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__host__
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void groestlcoin_cpu_hash(int thr_id, uint32_t threads, uint32_t startNounce, uint32_t *resNonce)
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{
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uint32_t threadsperblock = 256;
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// Compute 3.0 benutzt die registeroptimierte Quad Variante mit Warp Shuffle
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// mit den Quad Funktionen brauchen wir jetzt 4 threads pro Hash, daher Faktor 4 bei der Blockzahl
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int factor = 4;
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// berechne wie viele Thread Blocks wir brauchen
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dim3 grid(factor*((threads + threadsperblock-1)/threadsperblock));
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dim3 block(threadsperblock);
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int dev_id = device_map[thr_id];
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if (device_sm[dev_id] < 300 || cuda_arch[dev_id] < 300) {
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various fixes for SM 2.1 and the benchmark
X11+ algos and quark are not compatible for the moment
but these ones are :
Benchmark results for Gigabyte GTX 460 (SM 2.1 / 1 GB):
blakecoin : 159090.5 kH/s, 1 MB, 1048576 thr.
blake : 70208.9 kH/s, 1 MB, 1048576 thr.
bmw : 122802.6 kH/s, 65 MB, 2097152 thr.
deep : 3533.6 kH/s, 33 MB, 524288 thr.
fugue256 : 43177.9 kH/s, 17 MB, 524288 thr.
heavy : 4118.2 kH/s, 147 MB, 524032 thr.
keccak : 18673.1 kH/s, 129 MB, 2097152 thr.
luffa : 28816.0 kH/s, 257 MB, 4194304 thr.
lyra2 : 213.7 kH/s, 570 MB, 65536 thr.
mjollnir : 3895.6 kH/s, 147 MB, 524032 thr.
nist5 : 1101.4 kH/s, 67 MB, 1048576 thr.
penta : 501.6 kH/s, 21 MB, 327680 thr.
skein : 5432.4 kH/s, 65 MB, 1048576 thr.
skein2 : 6788.9 kH/s, 33 MB, 524288 thr.
whirlpool : 688.5 kH/s, 33 MB, 524288 thr.
zr5 : 122.5 kH/s, 86 MB, 262144 thr.
9 years ago
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gpulog(LOG_ERR, thr_id, "Sorry, This algo is not supported by this GPU arch (SM 3.0 required)");
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proper_exit(EXIT_CODE_CUDA_ERROR);
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}
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cudaMemset(d_resultNonce[thr_id], 0xFF, sizeof(uint32_t));
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groestlcoin_gpu_hash_quad <<<grid, block>>> (threads, startNounce, d_resultNonce[thr_id]);
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// Strategisches Sleep Kommando zur Senkung der CPU Last
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// MyStreamSynchronize(NULL, 0, thr_id);
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cudaMemcpy(resNonce, d_resultNonce[thr_id], sizeof(uint32_t), cudaMemcpyDeviceToHost);
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}
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